As the project evolves, it promises to redefine dietary management, making healthy choices more accessible, accurate, and ...

Artificial Intelligence (AI) is significantly transforming the material testing industry by introducing new levels of ...

Prediction of After-Sales Behavior in E-Commerce Using Machine Learning Models. Open Journal of Statistics, 14, 757-774. doi: ...

The core idea of WiMi's Machine Learning-Based Quantum Error Suppression Technology (MLQES) is to predict potential errors in quantum circuits using machine learning models and dynamically adjust the ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar ...

With AI taking more and more space in biotech, CRISPR stands out as one of the most promising avenues for AI integration.

The magic of AI lies in its ability to learn and act - training develops the brain and inferencing puts it to work.

Researchers developed an AI debiasing technique that improves the fairness of a machine-learning model by boosting its performance for subgroups that are underrepresented in its training data, while ...

Please note that these are just the code examples accompanying the book, which we uploaded for your convenience; be aware that these notebooks may not be useful without the formulae and descriptive ...

To screen catalysts, scientists must understand systems’ adsorption energy, something that machine learning (ML) models, particularly graph neural networks (GNNs), have been successful at predicting.

and enabling data-driven precision oncology. In skin cancer, machine learning (ML) based models could classify skin cancer with an accuracy of 94.2 per cent, with a sensitivity and specificity greater ...